Dynamic strategy based parallel ant colony optimization on GPUs for TSPs




This work was supported by National Science Foundation of China (Grant Nos. 61472289, 61502353) and Hubei Province Science Foundation (Grant No. 2015CFB254). The authors thank Dr. Cecilia for providing the CUDA source code in [5], which is a great benchmark for comparison. Supporting information Appendixes A–C, including Algorithm B5, Tables C4 and C5. The supporting information is available online at and The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

Supplementary material

11432_2015_594_MOESM1_ESM.pdf (720 kb)
Dynamic strategy based parallel ant colony optimization on GPUs for TSPs


  1. 1.
    Blum C, Roli A. Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput Surv, 2003, 35: 268–308CrossRefGoogle Scholar
  2. 2.
    Dorigo M, Stützle T. Ant Colony Optimization. Cambridge: MIT Press, 2004. 65–90MATHGoogle Scholar
  3. 3.
    Alba E, Luque G, Nesmachnow S. Parallel metaheuristics: recent advances and new trends. Int Trans Oper Res, 2013, 20: 1–48CrossRefMATHGoogle Scholar
  4. 4.
    Uchida A, Ito Y, Nakano K. An efficient GPU implementation of ant colony optimization for the traveling salesman problem. In: Proceedings of the 2012 3rd International Conference on Networking and Computing (ICNC), Okinawa, 2012. 94–102CrossRefGoogle Scholar
  5. 5.
    Cecilia J M, Garcia J M, Nisbet A, et al. Enhancing data parallelism for ant colony optimization on GPUs. J Parallel Distr Com, 2013, 73: 42–51CrossRefGoogle Scholar
  6. 6.
    Dawson L, Stewart I. Improving ant colony optimization performance on the GPU using CUDA. In: Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC), Cancun, 2013. 1901–1908CrossRefGoogle Scholar
  7. 7.
    Zhou Y, He F Z, Qiu Y M. Optimization of parallel iterated local search algorithms on graphics processing unit. J Supercomput, 2016, 72: 2394–2416CrossRefGoogle Scholar
  8. 8.
    Wu Y Q, He F Z, Zhang D J, et al. Service-oriented feature-based data exchange for cloud-based design and manufacturing. IEEE Trans Serv Comput, 2016, doi: 10.1109/TSC.2015.2501981Google Scholar
  9. 9.
    Li K, He F Z, Chen X. Real time object tracking via compressive feature selection. Front Comput Sci-Chi, 2016, 10: 689–701CrossRefGoogle Scholar
  10. 10.
    Cheng Y, He F Z, Wu Y Q, et al. Meta-operation conflict resolution for human-human interaction in collaborative feature-based CAD systems. Cluster Comput, 2016, 19: 237–253CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.State Key Laboratory of Software Engineering, School of Computer ScienceWuhan UniversityWuhanChina
  2. 2.School of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  3. 3.School of Information Science and EngineeringWuhan University of Science and TechnologyWuhanChina

Personalised recommendations